Mean squared error performance of MFBD nonlinear scene reconstruction using speckle imaging in horizontal imaging applications

Terrestrial imaging over very long horizontal paths is increasingly common in surveillance and defense systems. All optical systems that operate in or through the atmosphere suffer from turbulence induced image blur. This paper explores the Mean-Square-Error (MSE) performance of a multi-frame-blind-deconvolution-based reconstruction technique using a non-linear optimization strategy to recover a reconstructed object. Three sets of 70 images representing low, moderate and severe turbulence degraded images were simulated from a diffraction limited image taken with a professional digital camera. Reconstructed objects showed significant, 54, 22 and 14 percent improvement in mean squared error for low, moderate, and severe turbulence cases respectively